Rights statement: This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The definitive publisher-authenticated version R J Smethurst, M Merrifield, C J Lintott, K L Masters, B D Simmons, A Fraser-McKelvie, T Peterken, M Boquien, R A Riffel, N Drory; SNITCH: seeking a simple, informative star formation history inference tool, Monthly Notices of the Royal Astronomical Society, Volume 484, Issue 3, 11 April 2019, Pages 3590–3603, https://doi.org/10.1093/mnras/stz239 is available online at: https://academic.oup.com/mnras/article/484/3/3590/5304624
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - SNITCH
T2 - seeking a simple, informative star formation history inference tool
AU - Smethurst, R J
AU - Merrifield, M
AU - Lintott, C J
AU - Masters, K L
AU - Simmons, B D
AU - Fraser-McKelvie, A
AU - Peterken, T
AU - Boquien, M
AU - Riffel, R A
AU - Drory, N
N1 - This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The definitive publisher-authenticated version R J Smethurst, M Merrifield, C J Lintott, K L Masters, B D Simmons, A Fraser-McKelvie, T Peterken, M Boquien, R A Riffel, N Drory; SNITCH: seeking a simple, informative star formation history inference tool, Monthly Notices of the Royal Astronomical Society, Volume 484, Issue 3, 11 April 2019, Pages 3590–3603, https://doi.org/10.1093/mnras/stz239 is available online at: https://academic.oup.com/mnras/article/484/3/3590/5304624
PY - 2019/4/11
Y1 - 2019/4/11
N2 - Deriving a simple, analytic galaxy star formation history (SFH) using observational data is a complex task without the proper tool to hand. We therefore present SNITCH, an open source code written in PYTHON, developed to quickly (2 min) infer the parameters describing an analytic SFH model from the emission and absorption features of a galaxy spectrum dominated by star formation gas ionization. SNITCH uses the Flexible Stellar Population Synthesis models of Conroy, Gunn & White (2009), the MaNGA Data Analysis Pipeline and a Markov Chain Monte Carlo method in order to infer three parameters (time of quenching, rate of quenching, and model metallicity) which best describe an exponentially declining quenching history. This code was written for use on the MaNGA spectral data cubes but is customizable by a user so that it can be used for any scenario where a galaxy spectrum has been obtained, and adapted to infer a user defined analytic SFH model for specific science cases. Herein, we outline the rigorous testing applied to SNITCH and show that it is both accurate and precise at deriving the SFH of a galaxy spectra. The tests suggest that SNITCHis sensitive to the most recent epoch of star formation but can also trace the quenching of star formation even if the true decline does not occur at an exponential rate. With the use of both an analytical SFH and only five spectral features, we advocate that this code be used as a comparative tool across a large population of spectra, either for integral field unit data cubes or across a population of galaxy spectra.
AB - Deriving a simple, analytic galaxy star formation history (SFH) using observational data is a complex task without the proper tool to hand. We therefore present SNITCH, an open source code written in PYTHON, developed to quickly (2 min) infer the parameters describing an analytic SFH model from the emission and absorption features of a galaxy spectrum dominated by star formation gas ionization. SNITCH uses the Flexible Stellar Population Synthesis models of Conroy, Gunn & White (2009), the MaNGA Data Analysis Pipeline and a Markov Chain Monte Carlo method in order to infer three parameters (time of quenching, rate of quenching, and model metallicity) which best describe an exponentially declining quenching history. This code was written for use on the MaNGA spectral data cubes but is customizable by a user so that it can be used for any scenario where a galaxy spectrum has been obtained, and adapted to infer a user defined analytic SFH model for specific science cases. Herein, we outline the rigorous testing applied to SNITCH and show that it is both accurate and precise at deriving the SFH of a galaxy spectra. The tests suggest that SNITCHis sensitive to the most recent epoch of star formation but can also trace the quenching of star formation even if the true decline does not occur at an exponential rate. With the use of both an analytical SFH and only five spectral features, we advocate that this code be used as a comparative tool across a large population of spectra, either for integral field unit data cubes or across a population of galaxy spectra.
U2 - 10.1093/mnras/stz239
DO - 10.1093/mnras/stz239
M3 - Journal article
VL - 484
SP - 3590
EP - 3603
JO - Monthly Notices of the Royal Astronomical Society
JF - Monthly Notices of the Royal Astronomical Society
SN - 0035-8711
IS - 3
ER -